Efficient audio coding systems are generally those that could optimally eliminate irrelevant and redundant parts of an audio stream. Conventionally, the first is achieved by reducing psychoacoustical irrelevancy through psychoacoustics analysis. The term “perceptual audio coder” was coined to refer to those compression schemes that exploit the properties of human auditory perception. Further reduction is obtained from redundancy reduction.
Conventional psychoacoustics analysis generates masking thresholds on the basis of a psychoacoustic model of human hearing and aural perception. Psychoacoustic modeling typically takes into account the frequency-dependent thresholds of human hearing and a psychoacoustic phenomenon referred to as masking, whereby a strong frequency component close to one or more weaker frequency components tends to mask the weaker components, rendering them inaudible to a human listener. This makes it possible to omit the weaker frequency components when encoding audio signal, and thereby achieve a higher degree of compression, without adversely affecting the perceived quality of the encoded audio data stream. The masking data comprises a signal-to-mask ratio value for each frequency sub-band from the filter bank. These signal-to-mask ratio values represent the amount of signal masked by the human ear in each frequency sub-band, and are therefore also referred to as masking thresholds.
There is therefore a need for improved systems and methods for encoding audio data.